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Update app.py
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app.py
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@@ -3,6 +3,7 @@ import spaces
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
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from fastapi import FastAPI, HTTPException
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import uvicorn
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import json
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@@ -13,17 +14,25 @@ app = FastAPI()
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CHECKPOINT = "bigcode/starcoder2-15b"
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DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
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# Load model and tokenizer with
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@spaces.GPU(duration=120)
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def load_model_and_generate(prompt, max_length=256, temperature=0.2, top_p=0.95):
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try:
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# Initialize tokenizer
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tokenizer = AutoTokenizer.from_pretrained(CHECKPOINT)
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#
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model = AutoModelForCausalLM.from_pretrained(
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CHECKPOINT,
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device_map="auto"
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)
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@@ -32,8 +41,7 @@ def load_model_and_generate(prompt, max_length=256, temperature=0.2, top_p=0.95)
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"text-generation",
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model=model,
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tokenizer=tokenizer,
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device_map="auto"
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torch_dtype=torch.bfloat16
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)
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# Format prompt for chat-like interaction
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@@ -80,7 +88,7 @@ async def backdoor_chat(request: dict):
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# Gradio interface setup
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with gr.Blocks() as demo:
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gr.Markdown("# StarCoder2-15B Chat Interface")
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gr.Markdown("Enter a prompt to generate code or simulate a chat. Use the API endpoint `/backdoor-chat` for programmatic access.")
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# Input components
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
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from fastapi import FastAPI, HTTPException
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from transformers import BitsAndBytesConfig
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import uvicorn
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import json
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CHECKPOINT = "bigcode/starcoder2-15b"
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DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
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# Load model and tokenizer with 4-bit quantization
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@spaces.GPU(duration=120)
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def load_model_and_generate(prompt, max_length=256, temperature=0.2, top_p=0.95):
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try:
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# Initialize tokenizer
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tokenizer = AutoTokenizer.from_pretrained(CHECKPOINT)
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# Configure 4-bit quantization
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quantization_config = BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_compute_dtype=torch.bfloat16,
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bnb_4bit_quant_type="nf4",
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bnb_4bit_use_double_quant=True
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)
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# Initialize model with rs
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model = AutoModelForCausalLM.from_pretrained(
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CHECKPOINT,
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quantization_config=quantization_config,
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device_map="auto"
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)
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"text-generation",
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model=model,
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tokenizer=tokenizer,
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device_map="auto"
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)
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# Format prompt for chat-like interaction
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# Gradio interface setup
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with gr.Blocks() as demo:
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gr.Markdown("# StarCoder2-15B Chat Interface (4-bit Quantization)")
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gr.Markdown("Enter a prompt to generate code or simulate a chat. Use the API endpoint `/backdoor-chat` for programmatic access.")
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# Input components
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